API v1.0 DocumentationNEW

Supercharge Your AI with VoltageGPU API

Introduction

RESTful API

Our API follows REST principles with predictable resource-oriented URLs, standard HTTP verbs, and JSON responses for seamless integration.

Version Control

API versioning ensures backward compatibility. Always use the latest stable version for new projects to access the newest features.

Webhooks

Real-time event notifications keep your application in sync with GPU instance states, billing events, and system updates.

Base URL & Endpoints

Production Environment
https://api.voltagegpu.com/v1
All API requests must be made over HTTPS. Calls made over plain HTTP will be rejected.

Authentication & Security

Secure your API requests with our token-based authentication system. Generate and manage API keys from your dashboard with granular permissions.

1

Generate API Key

Create keys in your dashboard

2

Add to Headers

Include in Authorization header

3

Make Requests

Start using the API

Authorization Header Format
Authorization: Bearer YOUR_API_KEY_HERE
Security Best Practices:
  • Never expose API keys in client-side code or public repositories
  • Use environment variables to store sensitive credentials
  • Rotate keys regularly and revoke unused ones
  • Set IP whitelist and rate limits for production keys

Quick Start Guide

Create your first GPU instance in seconds

Choose your preferred programming language and follow our interactive examples to deploy your first GPU instance.

curl -X POST https://api.voltagegpu.com/v1/compute/instances \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "gpu_type": "RTX_4090",
    "gpu_count": 4,
    "region": "us-east-1",
    "image": "pytorch:latest"
  }'
Need help? Check our interactive tutorials or join our Discord community.

Core Resources

Explore our comprehensive API resources for GPU compute, AI generation, and more

GPU Instances

Deploy and manage high-performance GPU instances with support for RTX 4090, A100, H100, and latest models.

Auto-scalingMulti-GPUCustom Images
Explore Documentation

Compute Tasks

Run containerized workloads with full Docker and Kubernetes support for scalable ML training and inference.

Batch ProcessingDistributedOrchestration
Explore Documentation

AI Generation

Generate images, videos, and other content using state-of-the-art AI models powered by our GPU infrastructure.

Stable DiffusionLLMsCustom Models
Explore Documentation

Templates

Use pre-configured templates for common workloads or create custom templates for your specific requirements.

One-click DeployCustom ConfigVersion Control
Explore Documentation

HTTP Response Codes

VoltageGPU uses conventional HTTP response codes to indicate the success or failure of API requests. Codes in the 2xx range indicate success, 4xx indicate client errors, and 5xx indicate server errors.

Success Codes

200
OK

Request completed successfully

201
Created

Resource created successfully

204
No Content

Request succeeded with no response body

Client Errors

400
Bad Request

Invalid request parameters

401
Unauthorized

Missing or invalid API key

403
Forbidden

Insufficient permissions

404
Not Found

Resource doesn't exist

429
Too Many Requests

Rate limit exceeded

Server Errors

500
Internal Server Error

Server encountered an error

503
Service Unavailable

Service temporarily offline

Next Steps